#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union#> # A tibble: 1 × 2
#> late_integration GlobalScore
#> <chr> <dbl>
#> 1 limean 0.553#> # A tibble: 2 × 2
#> early_integration GlobalScore
#> <chr> <dbl>
#> 1 OnlyMet 0.661
#> 2 OnlyRna 0.359boxplots_fsMET_mae = ggplot(results_li, aes(x = feature_selection_mixMET, y = mae, fill = feature_selection_mixMET)) +
geom_boxplot() + facet_wrap(~ dataset, scales = “free_x”) + theme( axis.text.x = element_text(angle = 45, hjust = 1, size = 8), panel.border = element_rect(color = “black”, fill = NA, linewidth = 0.5), plot.title = element_text(hjust = 0.5), legend.position = “bottom” ) + labs( title = “Estimation error (-> 0), per dataset”, x = “Methods”, y = “MAE”, fill = “Feature selection for mixMET” ) plotly::layout( plotly::ggplotly(boxplots_fsMET_mae), # boxmode = “group”, legend = list( # x = 0, # y = -0.3, # xanchor = ‘left’, # yanchor = ‘bottom’, orientation = ‘h’) )
boxplots_fsRNA_mae = ggplot(results_li, aes(x = feature_selection_mixRNA, y = mae, fill = feature_selection_mixRNA)) + geom_boxplot() + facet_wrap(~ dataset, scales = “free_x”) + theme( axis.text.x = element_text(angle = 45, hjust = 1, size = 8), panel.border = element_rect(color = “black”, fill = NA, linewidth = 0.5), plot.title = element_text(hjust = 0.5), legend.position = “bottom” ) + labs( title = “Estimation error (-> 0), per dataset”, x = “Methods”, y = “MAE”, fill = “Feature selection for mixRNA:” ) plotly::layout( plotly::ggplotly(boxplots_fsRNA_mae), # boxmode = “group”, legend = list( # x = 0, # y = -0.3, # xanchor = ‘left’, # yanchor = ‘bottom’, orientation = ‘h’) )
### LI
```{=html}
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